{"id":"W2170817139","doi":"10.1002/gbc.20029","title":"Revisiting “nutrient trapping” in global coupled biogeochemical ocean circulation models","year":2013,"lang":"en","type":"article","venue":"Global Biogeochemical Cycles","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":107,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft; University of Victoria","keywords":"Biogeochemical cycle; Ocean current; Biogeochemistry; Oceanography; Environmental science; Nutrient; Ocean general circulation model; Trapping; Climatology; Atmospheric sciences; General Circulation Model; Chemistry; Geology; Ecology; Climate change; Biology; Environmental chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002072594,0.0002926631,0.0003715581,0.00004699807,0.0000860638,0.0001476267,0.0003366891,0.0002295958,0.0008359288],"category_scores_gemma":[0.00007969209,0.0002666852,0.0001558324,0.0007254306,0.00009412362,0.0003837155,0.00006438079,0.0001579194,0.000297236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006799265,"about_ca_system_score_gemma":0.00005354741,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02229691,"about_ca_topic_score_gemma":0.00068066,"domain_scores_codex":[0.9976653,0.00006419588,0.0005956133,0.0005754566,0.000431477,0.0006679363],"domain_scores_gemma":[0.9991428,0.00006245716,0.0001311011,0.0002644499,0.00008491513,0.0003142265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000409706,0.00004687248,0.9773545,0.00005929128,0.00002024777,0.00001539441,0.00001673231,0.0007065588,0.0007616,0.0008904003,0.0009300587,0.01915736],"study_design_scores_gemma":[0.001385232,0.00006733756,0.3302036,0.0002449578,0.00003776603,0.0001220612,0.0003429086,0.4697945,0.00108566,0.1945203,0.001156578,0.00103912],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815944,0.0007869965,0.0001428329,0.0005846066,0.0001193555,0.0003875493,0.0006338257,0.0001207453,0.01562965],"genre_scores_gemma":[0.998109,0.00004440265,0.0003043736,0.0002251048,0.0001983423,0.000004060018,0.001108326,0.000003519687,0.000002873514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6471509,"threshold_uncertainty_score":0.9999785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01256352799414325,"score_gpt":0.2107503381308936,"score_spread":0.1981868101367503,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}